Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.egypro.2017.07.400
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dc.titleThe Building Data Genome Project: An open, public data set from non-residential building electrical meters
dc.contributor.authorMiller, Clayton
dc.contributor.authorMeggers, Forrest
dc.date.accessioned2021-04-16T06:37:36Z
dc.date.available2021-04-16T06:37:36Z
dc.date.issued2017-01-01
dc.identifier.citationMiller, Clayton, Meggers, Forrest (2017-01-01). The Building Data Genome Project: An open, public data set from non-residential building electrical meters. 7th International Conference on Future Buildings and Districts - Energy Efficiency from Nano to Urban Scale (CISBAT) 122 : 439-444. ScholarBank@NUS Repository. https://doi.org/10.1016/j.egypro.2017.07.400
dc.identifier.issn18766102
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/189464
dc.description.abstractAs of 2015, there are over 60 million smart meters installed in the United States; these meters are at the forefront of big data analytics in the building industry. However, only a few public data sources of hourly non-residential meter data exist for the purpose of testing algorithms. This paper describes the collection, cleaning, and compilation of several such data sets found publicly on-line, in addition to several collected by the authors. There are 507 whole building electrical meters in this collection, and a majority are from buildings on university campuses. This group serves as a primary repository of open, non-residential data sources that can be built upon by other researchers. An overview of the data sources, subset selection criteria, and details of access to the repository are included. Future uses include the application of new, proposed prediction and classification models to compare performance to previously generated techniques.
dc.publisherELSEVIER SCIENCE BV
dc.sourceElements
dc.subjectOpen Data
dc.subjectNon-Residential Building Meter Data
dc.subjectBenchmark Data Set
dc.subjectBig Data
dc.subjectMachine Learning
dc.typeConference Paper
dc.date.updated2021-04-15T03:28:56Z
dc.contributor.departmentDEPT OF ARCHITECTURE
dc.contributor.departmentDEPT OF BUILDING
dc.description.doi10.1016/j.egypro.2017.07.400
dc.description.sourcetitle7th International Conference on Future Buildings and Districts - Energy Efficiency from Nano to Urban Scale (CISBAT)
dc.description.volume122
dc.description.page439-444
dc.published.statePublished
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